What the Thai Cave Rescue Teaches Us About Outcome Prediction

The world rejoiced as the remaining four members of the Wild Boars soccer team and their coach emerged from the Tham Luang Cave on July 10th. The 18-day rescue operation riveted people from around the globe as we anxiously watched, waited and hoped for what seemed like the impossible—a happy ending.

Thanks to the tireless dedication and bravery of many (including the ultimate sacrifice of one), careful planning, and precise execution, all 13 were brought to safety. And all of us—near and far—let out a collective exhale of joy and relief as we celebrated the long-awaited close of a successful operation.

Successful outcomes—especially perilous missions with such high stakes—don’t just happen. Many factors are at play, but one that cannot be overstated is the importance of “what/if” scenario planning.

In the Thai Cave Rescue, many scenarios were analyzed. Should the rescue begin immediately; in a few days; or even months at the end of monsoon season? What’s the best route and strategy for support divers? Who should be rescued first—the strongest or the weakest? And the list goes on.

These types of questions require quick and precise analysis, so leaders can determine the option with the best possible outcome and lowest associated risk. At Qlik’s recent Federal Summit in Washington, DC, William Busch, Analysis Division Chief at Army G-2 and Brian Frutchey, Vice President at NuWave, discussed the role of Army intelligence in achieving mission readiness. It’s a concept Busch calls “Winds of War” and centers around risk reduction as a key component to readiness.

Busch says, “If I can help [the Chief of Staff] mitigate risk, I can help him have the right army, at the right time, in the right place and right context.” The idea centers around moving the decision process for the army to the left—predicting likely outcomes for various scenarios. The ‘what/where’, he explains, “has to be augmented by IT or it’s not going to go anywhere.”

Using Qlik and a machine learning platform, Celect, Frutchey detailed one example of how they did just that. By integrating Qlik and Celect, they identified Army resource and staffing models for future conflicts.

“We took 65 different data sources, correlated with machine learning, and integrated all these data sources to let senior leaders see insights they need quickly. And we did it in less than a week.”

Whether responding to a military threat, or performing a complex rescue mission like in the Tham Luang Cave, the ability to predict likely outcomes is essential to achieving readiness. And where readiness is concerned, outcomes matter. To everyone on the Thai Cave Rescue team who had a hand in ensuring mission success—Thai Navy Seals, Australian and British Divers, medics and support staff—well done. The world thanks you.

With the #ThaiCaveRescue coming to and end, @Hgittings discusses the importance of integrating analytics in scenario planning.